Recently, due to the development of vehicle navigation techniques and the rapid development of automated driving techniques of vehicles, more attention has been paid to the use of probe information obtained from probe vehicles in order to provide more detailed map and road status information. However, depending on the probe information's target region and target period, the probe information data volume may grow to a petabyte scale because the number of the probe information items is very large and the volume of information included in each of the probe information items is also very large. Therefore, the system resources load for processing the above data volume has been increased further.
There are well known techniques, in which point cloud data sets representing positions and shapes of target objects are given, as votes, to each of the divided spaces (voxels) that are made by dividing a three-dimensional space into predetermined-sized spaces, and then the given point cloud data sets are converted into data for the respective voxels.